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Empirical Study on the Effects of Technology Training on the Forest-Related Income of Rural Poverty-Stricken Households—Based on the PSM Method

Author

Listed:
  • Rong Zhao

    (Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing 100091, China)

  • Xiaolu Qiu

    (Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing 100091, China)

  • Shaozhi Chen

    (Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing 100091, China)

Abstract

The implementation of technology training is essential to promote the commercialization of research achievements, and plays a crucial role in poverty alleviation in China. Based on the microcosmic survey data of farmers in four poverty-stricken counties officially assisted by National Forestry and Grassland Administration, the effects of technology training on forest-related income of rural poverty-stricken households is analyzed by using Propensity Score Matching (PSM) method. The study found that after eliminating the deviation from the self-selection and the endogenous issues, the forestry technology training has increased the total forest-related family income and forestry production and operation income by 3.09 times and 2.82 times, respectively. The effect of technology training on income increase is remarkable. Besides, the behavior of poor farmers participating in forestry technology training is significantly affected by the following factors, such as gender, age, family size, managed forestland area, whether they held forest tenure/equity certificate, whether they joined forestry professional cooperatives, and whether they cooperated with forestry enterprises. In order to further improve the effect of technology in poverty alleviation, the following policy recommendations are proposed, including: (1) to encourage poverty-stricken households to actively participate in forestry technology training; (2) to establish a diversified system of forestry technology training; and (3) to ensure the training content is based on the actual needs of the poor.

Suggested Citation

  • Rong Zhao & Xiaolu Qiu & Shaozhi Chen, 2021. "Empirical Study on the Effects of Technology Training on the Forest-Related Income of Rural Poverty-Stricken Households—Based on the PSM Method," Sustainability, MDPI, vol. 13(13), pages 1-12, June.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7143-:d:582093
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    References listed on IDEAS

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    6. Schreinemachers, Pepijn & Wu, Mei-huey & Uddin, Md. Nasir & Ahmad, Shahabuddin & Hanson, Peter, 2016. "Farmer training in off-season vegetables: Effects on income and pesticide use in Bangladesh," Food Policy, Elsevier, vol. 61(C), pages 132-140.
    7. He, Xu & Sakurai, Takeshi, 2019. "Transferability of Green Revolution in Sub-Saharan Africa: Impact Assessment of Rice Production Technology Training in Northern Ghana," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 21.
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    1. Rong Zhao & Tianyu Jia & He Li, 2023. "Could the Sloping Land Conversion Program Promote Farmers’ Income in Rocky Desertification Areas?—Evidence from China," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    2. Yuewen Huo & Songlin Ye & Zhou Wu & Fusuo Zhang & Guohua Mi, 2022. "Barriers to the Development of Agricultural Mechanization in the North and Northeast China Plains: A Farmer Survey," Agriculture, MDPI, vol. 12(2), pages 1-14, February.

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